class_docstr: This class will fill gaps in the source data using the following
  information bits from the underlying data source
  
    - timeframe and compression to dimension the output bars
  
    - sessionstart and sessionend
  
  If a data feed has missing bars in between 10:31 and 10:34 and the
  timeframe is minutes, the output will be filled with bars for minutes
  10:32 and 10:33 using the closing price of the last bar (10:31)
  
  Bars can be missinga amongst other things because
  
  Params:
    - ``fill_price`` (def: None): if None (or evaluates to False),the
      closing price will be used, else the passed value (which can be
      for example 'NaN' to have a missing bar in terms of evaluation but
      present in terms of time
  
    - ``fill_vol`` (def: NaN): used to fill the volume of missing bars
  
    - ``fill_oi`` (def: NaN): used to fill the openinterest of missing bars
code: def _frombars(self):
      dtime, price = self._fillbars.popleft()
  
      price = self.p.fill_price or price
  
      self.lines.datetime[0] = self.p.dataname.date2num(dtime)
      self.lines.open[0] = price
      self.lines.high[0] = price
      self.lines.low[0] = price
      self.lines.close[0] = price
      self.lines.volume[0] = self.p.fill_vol
      self.lines.openinterest[0] = self.p.fill_oi
  
      return True
  
file_path: backtrader/backtrader/filters/datafiller.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import collections
  from datetime import datetime, timedelta
  from backtrader import AbstractDataBase, TimeFrame
label_desc: Use image node_id 4 for calling the DataFiller obj's underlying member method code with example usage: obj._frombars() and returns: True